{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Wine.ipynb","provenance":[],"collapsed_sections":["4Rdr7oo8PqDs","WCusRAq5Pslr","4tjxiyOkPvFR"],"toc_visible":true,"mount_file_id":"1px8d-QMmVRfLYNJoAFgYxasBln_iKcBz","authorship_tag":"ABX9TyPKXtXEBfvwSSWM2WGBDOVK"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"JwmVOKDdeYGB","colab_type":"code","colab":{}},"source":["#ci permette di importare qualsiasi modulo\n","import sys\n","sys.path.append('/content/drive/My Drive/Colab Notebooks/TensorFlow 2.0/modules')\n","import pandas as pd\n","import tf_dataset_extractor as e\n","#import grapher_v1_1 as g\n","#import LSTM_creator_v1_0 as l\n","v = e.v\n","g = e.g\n","l = e.l"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Jgv54hgvMlBs","colab_type":"code","colab":{}},"source":["v.upload.offline_csv()\n","e.K = v.upload.make_backup()"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"4Rdr7oo8PqDs","colab_type":"text"},"source":["#Graph"]},{"cell_type":"code","metadata":{"id":"ufUTYSD0ZDCS","colab_type":"code","colab":{}},"source":["import pandas as np\n","v.upload.retrieve_backup(e.K)\n","e.X.hist(figsize=(15, 15), grid=False)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Bayp2RDZ_513","colab_type":"code","outputId":"464d9efd-6a91-4b40-8732-953750ccf598","executionInfo":{"status":"ok","timestamp":1587582227841,"user_tz":-120,"elapsed":3686,"user":{"displayName":"Michelangiolo Mazzeschi","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ghg8l8QeAQA6fd1iPVc2f_F0XQpum7zRjrF4R7HRw=s64","userId":"15738155355555420240"}},"colab":{"base_uri":"https://localhost:8080/","height":949}},"source":["import pandas as pd\n","import seaborn as sns\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import matplotlib\n","#a = sn.heatmap(e.X.corr(), annot=True)\n","\n","corr = e.X.corr()\n","\n","fig, ax = plt.subplots(figsize=(15,15)) \n","\n","# Generate a mask for the upper triangle\n","#mask = np.triu(np.ones_like(corr, dtype=np.bool))\n","#ax.set_facecolor((.21875, .21875, .21875))\n","\n","print(matplotlib.colors.to_rgb('black'))\n","\n","ax = sns.heatmap(\n","    corr,\n","    #mask=mask,\n","    vmin=-1, vmax=1, center=0,\n","    cmap=sns.diverging_palette(0, 256, n=200),\n","    square=True,\n","    ax=ax,\n","    annot=True\n",")"],"execution_count":0,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n","  import pandas.util.testing as tm\n"],"name":"stderr"},{"output_type":"stream","text":["(0.0, 0.0, 0.0)\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x1080 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"blBqYCFrKhZH","colab_type":"code","colab":{}},"source":["v.upload.retrieve_backup(e.K)\n","#v.upload.remove(['quality'])\n","corr = e.X.corr()\n","df = pd.DataFrame(corr.values)\n","df = df.to_numpy()\n","\n","df = df.reshape(144, )\n","df = pd.DataFrame(df)\n","df = df[df[0] != 1.0] \n","df.hist(bins=20, figsize=(15,15), grid=False)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"WCusRAq5Pslr","colab_type":"text"},"source":["#Preprocessing"]},{"cell_type":"code","metadata":{"id":"s16Bhnozenh5","colab_type":"code","outputId":"c14377f8-7188-45c5-eee4-bda991f15136","executionInfo":{"status":"ok","timestamp":1587816678846,"user_tz":-120,"elapsed":1028,"user":{"displayName":"Michelangiolo Mazzeschi","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ghg8l8QeAQA6fd1iPVc2f_F0XQpum7zRjrF4R7HRw=s64","userId":"15738155355555420240"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["v.upload.retrieve_backup(e.K)\n","v.partition.label_encoder(['quality'], to_float=True)\n","#v.extract.labels(['quality'])\n","v.partition.one_hot(['quality'])\n","v.extract.labels(['quality_0.0', 'quality_1.0', 'quality_2.0', 'quality_3.0', 'quality_4.0', 'quality_5.0'])\n","e.y.head()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>quality_0.0</th>\n","      <th>quality_1.0</th>\n","      <th>quality_2.0</th>\n","      <th>quality_3.0</th>\n","      <th>quality_4.0</th>\n","      <th>quality_5.0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   quality_0.0  quality_1.0  quality_2.0  quality_3.0  quality_4.0  quality_5.0\n","0            0            0            1            0            0            0\n","1            0            0            1            0            0            0\n","2            0            0            1            0            0            0\n","3            0            0            0            1            0            0\n","4            0            0            1            0            0            0"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"code","metadata":{"id":"B-OqBD8p1peA","colab_type":"code","outputId":"e598adc3-bf91-4002-d812-96f2f063d056","executionInfo":{"status":"ok","timestamp":1587816682209,"user_tz":-120,"elapsed":953,"user":{"displayName":"Michelangiolo Mazzeschi","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ghg8l8QeAQA6fd1iPVc2f_F0XQpum7zRjrF4R7HRw=s64","userId":"15738155355555420240"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["#k = lambda x : x - 2\n","#v.partition.edit_continuous(['quality'], k)\n","scaler, e.X = v.partition.scale('all_df', scaler='MinMaxScaler', df=e.X, to_float=True, return_df=True)\n","#scaler, e.X = v.partition.scale('all_df', df=e.X, to_float=True, return_df=True)\n","\n","e.X_numerical = e.X\n","e.X_categorical = pd.DataFrame()\n","X_train, X_test, y_train, y_test = v.cross_sectional_split(0.2, 14)\n","#scaler, X_train_norm = v.partition.scale(partitions='all_df', to_float=True, df=X_train, return_df=True)\n","#X_train.head()\n","X_train.head()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>fixed acidity</th>\n","      <th>volatile acidity</th>\n","      <th>citric acid</th>\n","      <th>residual sugar</th>\n","      <th>chlorides</th>\n","      <th>free sulfur dioxide</th>\n","      <th>total sulfur dioxide</th>\n","      <th>density</th>\n","      <th>pH</th>\n","      <th>sulphates</th>\n","      <th>alcohol</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>837</th>\n","      <td>0.185841</td>\n","      <td>0.109589</td>\n","      <td>0.28</td>\n","      <td>0.102740</td>\n","      <td>0.000000</td>\n","      <td>0.492958</td>\n","      <td>0.332155</td>\n","      <td>0.041847</td>\n","      <td>0.409449</td>\n","      <td>0.035928</td>\n","      <td>0.507692</td>\n","    </tr>\n","    <tr>\n","      <th>1103</th>\n","      <td>0.247788</td>\n","      <td>0.253425</td>\n","      <td>0.27</td>\n","      <td>0.082192</td>\n","      <td>0.098498</td>\n","      <td>0.183099</td>\n","      <td>0.067138</td>\n","      <td>0.279732</td>\n","      <td>0.480315</td>\n","      <td>0.179641</td>\n","      <td>0.553846</td>\n","    </tr>\n","    <tr>\n","      <th>503</th>\n","      <td>0.522124</td>\n","      <td>0.095890</td>\n","      <td>0.47</td>\n","      <td>0.068493</td>\n","      <td>0.110184</td>\n","      <td>0.070423</td>\n","      <td>0.063604</td>\n","      <td>0.552864</td>\n","      <td>0.346457</td>\n","      <td>0.425150</td>\n","      <td>0.384615</td>\n","    </tr>\n","    <tr>\n","      <th>348</th>\n","      <td>0.442478</td>\n","      <td>0.301370</td>\n","      <td>0.31</td>\n","      <td>0.130137</td>\n","      <td>0.128548</td>\n","      <td>0.197183</td>\n","      <td>0.141343</td>\n","      <td>0.574890</td>\n","      <td>0.291338</td>\n","      <td>0.353293</td>\n","      <td>0.246154</td>\n","    </tr>\n","    <tr>\n","      <th>670</th>\n","      <td>0.203540</td>\n","      <td>0.191781</td>\n","      <td>0.24</td>\n","      <td>0.109589</td>\n","      <td>0.118531</td>\n","      <td>0.408451</td>\n","      <td>0.137809</td>\n","      <td>0.428040</td>\n","      <td>0.409449</td>\n","      <td>0.149701</td>\n","      <td>0.246154</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["      fixed acidity  volatile acidity  ...  sulphates   alcohol\n","837        0.185841          0.109589  ...   0.035928  0.507692\n","1103       0.247788          0.253425  ...   0.179641  0.553846\n","503        0.522124          0.095890  ...   0.425150  0.384615\n","348        0.442478          0.301370  ...   0.353293  0.246154\n","670        0.203540          0.191781  ...   0.149701  0.246154\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"markdown","metadata":{"id":"4tjxiyOkPvFR","colab_type":"text"},"source":["#Random Forest Classifier + Tuning"]},{"cell_type":"code","metadata":{"id":"FfcTo_rlg9g1","colab_type":"code","colab":{}},"source":["#RandomForestClassifier\n","from sklearn.ensemble import RandomForestClassifier\n","clf = RandomForestClassifier(\n","  bootstrap=True,\n","  criterion='entropy',\n","  min_samples_split=3,\n","  n_estimators= 1400\n","  )\n","\n","param_grid = {\n","    'n_estimators': [1, 2, 3], \n","    'criterion': ['gini', 'entropy'],\n","    'min_samples_split': [2, 3, 4, 5],\n","    'bootstrap': [False, True]\n","}\n","\n","v.tuning(clf, param_grid, X_train, y_train)\n","#clf = clf.fit(X_train, y_train)\n","#y_predict = clf.predict(X_test)\n","#from sklearn.metrics import accuracy_score\n","#print(accuracy_score(y_test, y_predict))\n","\n","#X = pd.concat([X_train, X_test], axis=0)\n","#y = pd.concat([y_train, y_test], axis=0)\n","#v.cross_validation(clf, X, y, 10)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"d4bNdYl6jDRu","colab_type":"code","colab":{}},"source":["#predizione sul nostro split\n","clf = clf.fit(X_train, y_train)\n","y_predict = clf.predict(X_test)\n","from sklearn.metrics import accuracy_score\n","print(accuracy_score(y_test, y_predict))"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"EgIPBXX59zqd","colab_type":"code","colab":{}},"source":["#MOD\n","X = pd.concat([X_train, X_test], axis=0)\n","y = pd.concat([y_train, y_test], axis=0)\n","X.head()\n","cross_validation(clf, X, y, 10)\n","grid_search.best_params_\n","#y_predict = clf.predict(X_test)\n","from sklearn.metrics import accuracy_score\n","#print(accuracy_score(y_test, y_predict))"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"dJFrmdZpbAwV","colab_type":"text"},"source":["#MLP Classifier"]},{"cell_type":"code","metadata":{"id":"ejKdh4mVa_zx","colab_type":"code","colab":{}},"source":["%tensorflow_version 2.x\n","import tensorflow as tf\n","from tensorflow.keras import Sequential\n","from tensorflow.keras import layers\n","from tensorflow.keras.layers import Dense\n","from tensorflow.keras.layers import Dropout\n","from tensorflow.keras.layers import BatchNormalization\n","import matplotlib.pyplot as plt\n","print(tf.__version__)\n","from tensorflow.keras.optimizers import SGD\n","from tensorflow.keras.regularizers import l1\n","# instantiate regularizer\n","reg = l1(0.001)\n","model = Sequential()\n","model.add(Dense(250, activation='relu', kernel_initializer='he_normal', input_shape=(11, ), activity_regularizer=l1(0.002)))\n","model.add(BatchNormalization())\n","model.add(Dropout(0.8))\n","model.add(Dense(150, activation='relu', kernel_initializer='he_normal', activity_regularizer=l1(0.001)))\n","model.add(BatchNormalization())\n","model.add(Dropout(0.5))\n","model.add(Dense(90, activation='relu', kernel_initializer='he_normal', activity_regularizer=l1(0.001)))\n","model.add(BatchNormalization())\n","model.add(Dropout(0.2))\n","model.add(Dense(6, activation='softmax'))\n","# compile the model\n","opt = SGD(lr=0.15, momentum=0.09)\n","model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=['accuracy'])\n","# fit the model\n","history = model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=500, batch_size=32, verbose=2)\n","# evaluate the model\n","_, train_acc = model.evaluate(X_train, y_train, verbose=0)\n","_, test_acc = model.evaluate(X_test, y_test, verbose=0)\n","print('Train: %.3f, Test: %.3f' % (train_acc, test_acc))"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"1Trs_bjAk9l7","colab_type":"code","colab":{}},"source":["%tensorflow_version 2.x\n","import tensorflow as tf\n","from tensorflow.keras import Sequential\n","from tensorflow.keras import layers\n","!pip install keras-tuner\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"eyUPifM3jcX3","colab_type":"code","colab":{}},"source":["import kerastuner as kt\n","tuner = kt.Hyperband(\n","    build_model,\n","    objective='val_accuracy',\n","    max_epochs=30,\n","    hyperband_iterations=2)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Obpqe9Re9Wdk","colab_type":"code","outputId":"3b90622c-1b43-40b2-9d98-51020cf169cb","executionInfo":{"status":"ok","timestamp":1587809483529,"user_tz":-120,"elapsed":1197,"user":{"displayName":"Michelangiolo Mazzeschi","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ghg8l8QeAQA6fd1iPVc2f_F0XQpum7zRjrF4R7HRw=s64","userId":"15738155355555420240"}},"colab":{"base_uri":"https://localhost:8080/","height":281}},"source":["from matplotlib import pyplot\n","# plot loss during training\n","pyplot.subplot(211)\n","pyplot.title('Loss')\n","pyplot.plot(history.history['loss'], label='train')\n","pyplot.plot(history.history['val_loss'], label='test')\n","pyplot.legend()\n","# plot accuracy during training\n","pyplot.subplot(212)\n","pyplot.title('Accuracy')\n","pyplot.plot(history.history['accuracy'], label='train')\n","pyplot.plot(history.history['val_accuracy'], label='test')\n","pyplot.legend()\n","pyplot.show()\n","# make a prediction\n","#row = [5.1,3.5,1.4,0.2]\n","#yhat = model.predict([row])\n","#print('Predicted: %s (class=%d)' % (yhat, np.argmax(yhat)))"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"eeTlq56ejmi8","colab_type":"code","outputId":"a5f5757e-1c74-421c-c850-842eb8f73758","executionInfo":{"status":"ok","timestamp":1587589547380,"user_tz":-120,"elapsed":914,"user":{"displayName":"Michelangiolo Mazzeschi","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ghg8l8QeAQA6fd1iPVc2f_F0XQpum7zRjrF4R7HRw=s64","userId":"15738155355555420240"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["from sklearn.datasets import make_regression\n","from sklearn.datasets import make_circles\n","from sklearn.datasets import make_blobs\n","#generate regression dataset\n","a, b = make_regression(n_samples=1000, n_features=10, noise=0.1, random_state=1, n_targets=1)\n","# generate circles\n","a, b = make_circles(n_samples=1000, noise=0.1, random_state=1, factor=.9)\n","# generate dataset\n","a, b = make_blobs(n_samples=1000, centers=2, n_features=5, cluster_std=2, random_state=2)\n","\n","\n","\n","a = pd.DataFrame(a)\n","b = pd.DataFrame(b)\n","b.head()\n"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      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